Abstract
Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework for decision support systems (DSS) for the optimal planning and operation of a building infrastructure under appearing systemic de-regulations and risks. The DSS relies on a new two-stage, dynamic stochastic optimization model with moving random time horizons bounded by stopping time moments. This allows to model impacts of potential extreme events and structural changes emerging from a stakeholders dialogue, which may occur at any moment of the decision making process. The stopping time moments induce endogenous risk aversion in strategic decisions in a form of dynamic VaR-type systemic risk measures dependent on the system’s structure. The DSS implementation via an algebraic modeling language (AML) provides an environment that enforces the necessary stakeholders dialogue for robust planning and operation of a building infrastructure. Such a framework allows the representation and solution of building infrastructure systems optimization problems, to be implemented at the building level to confront rising systemic economic and environmental global changes.
Highlights
Energy systems optimization is increasing its importance due to de-regulations in energy sector and the setting of targets such as the European Union (EU) 20-20-20
Be obtained again; (2) in case other researchers have to contribute to the work, all the process is at hand; changes on any step of the process are made seamlessly just changing the appropriate data object, the whole analysis is made again with the new information, and the changes are automatically reflected in the output results; and (3) the results can be verified by independent reviewers
The model and decision support systems (DSS) presented in this paper have been tested using real data from the EnRiMa project
Summary
Energy systems optimization is increasing its importance due to de-regulations in energy sector and the setting of targets such as the European Union (EU) 20-20-20 (see Appendix “Literature review and background”). The model developed in this paper has moving time horizons defined by stopping time moments generated by potential extreme events and the stakeholders dialogue. This integrated framework provides an environment that enforces the necessary stakeholders communication. Regarding the dialogue among stakeholders (internal and external), it can take place at any point of the decision making process, and a user communication is crucial for the accurateness of the inputs. The developed framework provides a new flexible approach for DSS-based decision making process on optimal planning and operation of a building infrastructure in a dialogue with stakeholders.
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